Triple

T524633
Position Surface form Disambiguated ID Type / Status
Subject Keep a Child Alive E10891 entity
Predicate abbreviation P43 FINISHED
Object KCA
KCA is a nonprofit organization dedicated to providing life-saving HIV treatment, care, and support to children and families in underserved communities, particularly in Africa and India.
 E65017 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: KCA | Statement: [Keep a Child Alive, abbreviation, KCA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KCA
Context triple: [Keep a Child Alive, abbreviation, KCA]
  • A. KCB
    KCB is the post-nominal abbreviation for Knight Commander of the Order of the Bath, a senior British order of chivalry.
  • B. KC
    KC is a common shorthand nickname for Kansas City, Missouri, a major Midwestern U.S. city known for its jazz heritage, barbecue, and sports teams.
  • C. Kapor
    Kapor is the surname of Mitchell Kapor, an American entrepreneur best known for founding the software company Lotus Development Corporation.
  • D. KZ
    KZ is the two-letter ISO 3166-1 alpha-2 country code assigned to Kazakhstan for international standardization and identification.
  • E. Kawki
    Kawki is an indigenous Andean language closely related to Aymara and spoken by a small number of people in Peru.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: KCA
Triple: [Keep a Child Alive, abbreviation, KCA]
Generated description
KCA is a nonprofit organization dedicated to providing life-saving HIV treatment, care, and support to children and families in underserved communities, particularly in Africa and India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KCA
Target entity description: KCA is a nonprofit organization dedicated to providing life-saving HIV treatment, care, and support to children and families in underserved communities, particularly in Africa and India.
  • A. KCB
    KCB is the post-nominal abbreviation for Knight Commander of the Order of the Bath, a senior British order of chivalry.
  • B. KC
    KC is a common shorthand nickname for Kansas City, Missouri, a major Midwestern U.S. city known for its jazz heritage, barbecue, and sports teams.
  • C. Kapor
    Kapor is the surname of Mitchell Kapor, an American entrepreneur best known for founding the software company Lotus Development Corporation.
  • D. KZ
    KZ is the two-letter ISO 3166-1 alpha-2 country code assigned to Kazakhstan for international standardization and identification.
  • E. Kawki
    Kawki is an indigenous Andean language closely related to Aymara and spoken by a small number of people in Peru.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a2e84b16c4819088d284c47c3a7968 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f1b656c08190b387f21b06d99e68 completed Feb. 28, 2026, 1:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4ab224e008190b233b04b0a432b83 completed March 1, 2026, 9:09 p.m.
NEDg Description generation batch_69a4ab95938881908b05812e64ad9a6c completed March 1, 2026, 9:11 p.m.
NED2 Entity disambiguation (via description) batch_69a4ac05c7dc81908909da3a53671426 completed March 1, 2026, 9:13 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.